Description
HPE Labs is seeking a Principal AI Research Scientist for the HPE Quantum team within Emergent Machine Intelligence. As a senior individual-contributor role, you will focus on original, publication-driven research in areas including foundation model reasoning, representation learning, physics-inspired machine learning, mechanistic interpretability, and interdisciplinary work at the intersection of AI, quantum computing, and physical science.
Key Responsibilities:
- Independently lead research projects from initial brainstorming and problem formulation through mathematical development, implementation, experimentation, analysis, and publication.
- Translate early-stage ideas into concrete hypotheses and design rapid, decisive experiments to determine whether a direction should be expanded, revised, or discontinued.
- Produce original research suitable for publication at leading venues such as NeurIPS, ICML, ICLR, and comparable conferences and journals.
- Maintain broad and current knowledge of modern AI research and use that knowledge to identify emerging opportunities, relevant prior work, and meaningful open problems.
- Collaborate with researchers, engineers, interns, and external partners across AI, physics, quantum computing, and advanced computing systems.
- Develop and release reusable research assets, including open-source software, models, experimental infrastructure, benchmarks, or datasets, when appropriate.
Requirements:
- PhD in Computer Science, Artificial Intelligence, Machine Learning, Physics, Mathematics, or other related fields.
- Typically, 5+ years' experience Post PhD graduate studies.
- Strong and sustained record of original research in modern artificial intelligence or machine learning.
- Demonstrated ability to convert research ideas into rigorous, complete, and publishable outcomes, with a strong publication record at leading machine-learning venues.
- Broad and current command of the AI and machine-learning literature.
- Deep mathematical understanding of modern machine-learning methods.
- Excellent experimental skills.
- Advanced proficiency in Python and PyTorch.
- Experience working with research codebases, open-source libraries, HPC and distributed systems.
- Strong software-engineering and algorithm implementation skills.
- Strong written and verbal communication skills.
- Demonstrated ability to work autonomously and collaborate effectively in an interdisciplinary research environment.
Desired Knowledge and Skills:
- Substantial research background in theoretical physics, statistical physics, quantum physics, condensed-matter physics, or another mathematically intensive area of physics.
- Research experience combining machine learning with physics, applied mathematics, dynamical systems, optimization, or scientific computing.
- Experience moving fluidly between mathematical formulation, algorithm development, implementation, and empirical validation.
- Working proficiency in C++.
- Record of releasing high-quality open-source research software, models, benchmarks, datasets, or evaluation frameworks.
- Experience developing reusable experimental infrastructure or tools that accelerate research across multiple projects.
- Familiarity with neural quantum states, quantum many-body systems, quantum simulation, scientific machine learning, or other applications of AI to quantum science.
- Experience with advanced computational physics or chemistry methods.
What We Can Offer You:
- Health & Wellbeing benefits
- Personal & Professional Development programs
- Unconditional Inclusion